Abstract
In this paper, a novel cluster-based approach for optimizing the energy efficiency of wireless small cell networks is proposed. A dynamic mechanism based on the spectral clustering technique is proposed to dynamically form clusters of small cell base stations. Such clustering enables intra-cluster coordination among the base stations for optimizing the downlink performance through load balancing, while satisfying users' quality-of-service requirements. In the proposed approach, the clusters use an opportunistic base station sleep-wake switching mechanism to strike a balance between delay and energy consumption. The inter-cluster interference affects the performance of the clusters and their choices of active or sleep state. Due to the lack of inter-cluster communications, the clusters have to compete with each other to make decisions on improving the energy efficiency. This competition is formulated as a noncooperative game among the clusters that seek to minimize a cost function which captures the tradeoff between energy expenditure and load. To solve this game, a distributed learning algorithm is proposed using which the clusters autonomously choose their optimal transmission strategies. Simulation results show that the proposed approach yields significant performance gains in terms of reduced energy expenditures up to 40% and reduced load up to 23% compared to conventional approaches.
| Original language | English |
|---|---|
| Title of host publication | 2014 11th International Symposium on Wireless Communications Systems, ISWCS 2014 - Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 934-938 |
| Number of pages | 5 |
| ISBN (Print) | 9781479958634 |
| DOIs | |
| State | Published - Jan 1 2014 |
| Event | 2014 11th International Symposium on Wireless Communications Systems, ISWCS 2014 - Barcelona, Spain Duration: Aug 26 2014 → Aug 29 2014 |
Other
| Other | 2014 11th International Symposium on Wireless Communications Systems, ISWCS 2014 |
|---|---|
| Country | Spain |
| City | Barcelona |
| Period | 8/26/14 → 8/29/14 |
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Keywords
- Clustering
- energy efficiency
- game theory
- small cell networks
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Computer Networks and Communications
Cite this
Dynamic clustering and sleep mode strategies for small cell networks. / Samarakoon, Sumudu; Bennis, Mehdi; Saad, Walid; Latva-Aho, Matti.
2014 11th International Symposium on Wireless Communications Systems, ISWCS 2014 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. p. 934-938 6933487.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Dynamic clustering and sleep mode strategies for small cell networks
AU - Samarakoon, Sumudu
AU - Bennis, Mehdi
AU - Saad, Walid
AU - Latva-Aho, Matti
PY - 2014/1/1
Y1 - 2014/1/1
N2 - In this paper, a novel cluster-based approach for optimizing the energy efficiency of wireless small cell networks is proposed. A dynamic mechanism based on the spectral clustering technique is proposed to dynamically form clusters of small cell base stations. Such clustering enables intra-cluster coordination among the base stations for optimizing the downlink performance through load balancing, while satisfying users' quality-of-service requirements. In the proposed approach, the clusters use an opportunistic base station sleep-wake switching mechanism to strike a balance between delay and energy consumption. The inter-cluster interference affects the performance of the clusters and their choices of active or sleep state. Due to the lack of inter-cluster communications, the clusters have to compete with each other to make decisions on improving the energy efficiency. This competition is formulated as a noncooperative game among the clusters that seek to minimize a cost function which captures the tradeoff between energy expenditure and load. To solve this game, a distributed learning algorithm is proposed using which the clusters autonomously choose their optimal transmission strategies. Simulation results show that the proposed approach yields significant performance gains in terms of reduced energy expenditures up to 40% and reduced load up to 23% compared to conventional approaches.
AB - In this paper, a novel cluster-based approach for optimizing the energy efficiency of wireless small cell networks is proposed. A dynamic mechanism based on the spectral clustering technique is proposed to dynamically form clusters of small cell base stations. Such clustering enables intra-cluster coordination among the base stations for optimizing the downlink performance through load balancing, while satisfying users' quality-of-service requirements. In the proposed approach, the clusters use an opportunistic base station sleep-wake switching mechanism to strike a balance between delay and energy consumption. The inter-cluster interference affects the performance of the clusters and their choices of active or sleep state. Due to the lack of inter-cluster communications, the clusters have to compete with each other to make decisions on improving the energy efficiency. This competition is formulated as a noncooperative game among the clusters that seek to minimize a cost function which captures the tradeoff between energy expenditure and load. To solve this game, a distributed learning algorithm is proposed using which the clusters autonomously choose their optimal transmission strategies. Simulation results show that the proposed approach yields significant performance gains in terms of reduced energy expenditures up to 40% and reduced load up to 23% compared to conventional approaches.
KW - Clustering
KW - energy efficiency
KW - game theory
KW - small cell networks
UR - http://www.scopus.com/inward/record.url?scp=84911954836&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84911954836&partnerID=8YFLogxK
U2 - 10.1109/ISWCS.2014.6933487
DO - 10.1109/ISWCS.2014.6933487
M3 - Conference contribution
SN - 9781479958634
SP - 934
EP - 938
BT - 2014 11th International Symposium on Wireless Communications Systems, ISWCS 2014 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
ER -